---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: wav2vec2-base-music_genre_classifier-g3b
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-base-music_genre_classifier-g3b

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co./facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3709
- Accuracy: 0.7380
- F1: 0.7356
- Recall: 0.7395
- Precision: 0.7400

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 2.3444        | 1.0   | 276  | 2.2888          | 0.3618   | 0.2663 | 0.3495 | 0.2702    |
| 1.946         | 2.0   | 552  | 1.7679          | 0.4880   | 0.4277 | 0.4778 | 0.5072    |
| 1.6394        | 3.0   | 828  | 1.4655          | 0.5565   | 0.4966 | 0.5463 | 0.5089    |
| 1.2346        | 4.0   | 1104 | 1.3279          | 0.5974   | 0.5654 | 0.5937 | 0.6372    |
| 0.8945        | 5.0   | 1380 | 1.2718          | 0.6226   | 0.6021 | 0.6178 | 0.6240    |
| 0.7872        | 6.0   | 1656 | 1.1310          | 0.6671   | 0.6594 | 0.6691 | 0.6826    |
| 0.5562        | 7.0   | 1932 | 1.1743          | 0.6743   | 0.6677 | 0.6730 | 0.6857    |
| 0.65          | 8.0   | 2208 | 1.0722          | 0.7163   | 0.7178 | 0.7179 | 0.7394    |
| 0.3239        | 9.0   | 2484 | 1.1846          | 0.6899   | 0.6863 | 0.6909 | 0.6997    |
| 0.3885        | 10.0  | 2760 | 1.2243          | 0.7031   | 0.6994 | 0.7072 | 0.7126    |
| 0.1529        | 11.0  | 3036 | 1.2539          | 0.7175   | 0.7193 | 0.7195 | 0.7245    |
| 0.4527        | 12.0  | 3312 | 1.3231          | 0.7188   | 0.7116 | 0.7182 | 0.7220    |
| 0.324         | 13.0  | 3588 | 1.3190          | 0.7344   | 0.7360 | 0.7368 | 0.7409    |
| 0.0277        | 14.0  | 3864 | 1.3623          | 0.7356   | 0.7340 | 0.7370 | 0.7407    |
| 0.0276        | 15.0  | 4140 | 1.3709          | 0.7380   | 0.7356 | 0.7395 | 0.7400    |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3